chrisemoulton / althea

ALgoriTHms Exposed through a RESTful API

althea

ALgoriTHms Exposed through a RESTful API

althos: "healing"

Purpose

The purpose of this application is to make exposing algorithms via a RESTful API easier. After a clinical risk algorithm has been vetted, there are potentially many consumers of this algorithm. For instance, other researchers may be interested in coming up with new state-of-the-art algorithms, clinical operations may wish to use the algorithm to identify cohorts for studies, or in the case of computable phenotypes, real-time event detection. By exposing the algorithm via a RESTful API, we enable all consumers of the algorithm(s) to utilize the power of the algorithm. In the past, the algorithm had to be coded in whatever language each consumer used most often (e.g. SAS, PHP, JavaScript, etc.). Now each consumer can call one central source of truth, ensuring reproducibility and consistency.

##Installation

At this time, althea is purely a python package. It is our hope to allow submission of other types of code in the future. Two avenues for installation are available:

####github

git clone https://github.com/benneely/althea.git
cd ./althea
python setup.py install

####pip

pip install althea

API

---

The goal is to have ALTHEA available via two api's:

1. python
2. RESTful

Currently is is only available via (1)

Python API

To start playing with Althea, two risk algorithms can be loaded by default:

from althea import Metadata, Model
#add_examples is a named parameter that loads two algorithms that ship with Althea:
#Framingham 30 year CVD risk algorithm and the 2013 ACC/AHA Pooled Cohorts equation
models = Metadata(add_examples=True)
models_in_db = models.available_models()
#'deb9cc20-603f-4926-8ab9-66bb88d2ce0a'
#'cf8c7c12-0097-45ca-99cb-babcdd204d0e'

framingham = Model(models_in_db[0].get('model_uuid'))
framingham.score(sbp=120,male='No',smoke='Yes',tc=60,hdlc=110,age=33,diab='No',trtbp='No')